The emergence of the Internet of Things (IoT) and its applications has taken the attention of several researchers. In an effort to provide interoperability and IPv6 support for the IoT devices, the ...Internet Engineering Task Force (IETF) proposed the 6LoWPAN stack. However, the particularities and hardware limitations of networks associated with IoT devices lead to several challenges, mainly for routing protocols. On its stack proposal, IETF standardizes the RPL (IPv6 Routing Protocol for Low-Power and Lossy Networks) as the routing protocol for Low-power and Lossy Networks (LLNs). RPL is a tree-based proactive routing protocol that creates acyclic graphs among the nodes to allow data exchange. Although widely considered and used by current applications, different recent studies have shown its limitations and drawbacks. Among these, it is possible to highlight the weak support of mobility and P2P traffic, restrictions for multicast transmissions, and lousy adaption for dynamic throughput. Motivated by the presented issues, several new solutions have emerged during recent years. The approaches range from the consideration of different routing metrics to an entirely new solution inspired by other routing protocols. In this context, this work aims to present an extensive survey study about routing solutions for IoT/LLN, not limited to RPL enhancements. In the course of the paper, the routing requirements of LLNs, the initial protocols, and the most recent approaches are presented. The IoT routing enhancements are divided according to its main objectives and then studied individually to point out its most important strengths and weaknesses. Furthermore, as the main contribution, this study presents a comprehensive discussion about the considered approaches, identifying the still remaining open issues and suggesting future directions to be recognized by new proposals.
A new IoT‐based smart energy meter for smart grids Avancini, Danielly B.; Rodrigues, Joel J. P. C.; Rabêlo, Ricardo A. L. ...
International journal of energy research,
January 2021, 2021-01-00, 20210101, Letnik:
45, Številka:
1
Journal Article
Recenzirano
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Summary
The significant increase in energy consumption by the growth of the population or by the use of new equipment has brought big challenges to the energy security as well as the environment. ...There is a need that consumers can track their daily use and understand consumption standards for better organizing themselves to obtain financial and energetic efficiency. With the improvement of smart networks technology for better energy supply, a smart meter is not just a simple measurement gadget anymore, but it has additional functions including smart equipment control, bidirectional communication that allows integration of users and networks, and other functionalities. Smart meters are the most fundamental components in smart power grids. Besides, the meters used with a management system can be utilized for monitoring and controlling home appliances and other gadgets according to the users' need. A solution of an integrated and single system should be more efficient and economical. Smart measurement systems allow monitoring the energy consumption of the final consumers while providing useful information about the energy quality. The information provided by these systems is used by the operators to enhance the energy supply, and different techniques can be also applied for this end, such as charge scheduling, management from the demand side, and non‐intrusive load monitoring. The Internet of Things (IoT) is becoming a great ally in the management of smart distribution and energy consumption in smart systems scenarios. To address these issues, this paper proposes and demonstrates a new smart energy meter following an IoT approach and its associated costs and benefits. The developed device incorporates several communication interfaces. In order to easily integrate with any monitoring software solution, the meter has a multi‐protocol connection. Finally, the provided solution is validated and demonstrated in real‐life environments and it is also under use.
This paper proposes the design and implementation of a smart power meter following an Internet of Things (IoT) approach and integrated in an IoT middleware. The design provides an intelligent low‐power metering system. The proposed solution is installed at the end consumer for IoT operation, and it is capable to send commands and monitoring the quality of the power supply provided by the local utility. It is also possible to receive instant updates of any monitored variable failure. Data monitoring and management is performed through an IoT middleware called In.IoT. The solution is validated, demonstrated, and validated in real environments and it is under use.
Internet of Things (IoT) management systems require scalability, standardized communication, and context-awareness to achieve the management of connected devices with security and accuracy in real ...environments. Interoperability and heterogeneity between hardware and application layers are also critical issues. To attend to the network requirements and different functionalities, a dynamic and context-sensitive configuration management system is required. Thus, reference architectures (RAs) represent a basic architecture and the definition of key characteristics for the construction of IoT environments. Therefore, choosing the best technologies of the IoT management platforms and protocols through comparison and evaluation is a hard task, since they are difficult to compare due to their lack of standardization. However, in the literature, there are no management platforms focused on addressing all IoT issues. For this purpose, this paper surveys the available policies and solutions for IoT Network Management and devices. Among the available technologies, an evaluation was performed using features such as heterogeneity, scalability, supported technologies, and security. Based on this evaluation, the most promising technologies were chosen for a detailed performance evaluation study (through simulation and deployment in real environments). In terms of contributions, these protocols and platforms were studied in detail, the main features of each approach are highlighted and discussed, open research issues are identified as well as the lessons learned on the topic.
Demand Response (DR) aims to motivate end consumers to change their energy consumption patterns in response to changes in electricity prices or when the reliability of the electrical power system ...(EPS) is compromised. Most of the proposals found in the literature only aim at reducing the cost for end consumers. However, this article proposes a home energy management system (HEMS) that aims to schedule the use of each home appliance based on the price of electricity in real-time (RTP) and on the consumer satisfaction/comfort level in order to guarantee the stability and the safety of the EPS. Thus, this paper presents a multi-objective DR optimization model which was formulated as a multi-objective nonlinear programming problem subjected to a set of constraints and was solved using the Non-Dominated Sorted Genetic Algorithm (NSGA-II), in order to determine the scheduling of home appliances for the time horizon. The multi-objective DR optimization model not only to minimize the cost of electricity consumption but also to reduce the level of inconvenience for residential consumers. Moreover, a priori, it is expected to obtain a more uniform demand with fewer peaks in the system and, potentially, achieving a more reliable and safer EPS operation. Thus, the energy management controller (EMC) within the HEMS determines an optimized schedule for each home appliance through the multi-objective DR model presented in this article, and ensures a more economic scenario for end consumers. In this paper, a performance evaluation of HEMS in 15 Brazilian families between 1 January and 31 December 2016 is presented with different electric energy consumption patterns in the cities of Belém-PA, Teresina-PI, Cuiabá-MT, Florianópolis-SC and São Paulo-SP, with three families per city, located in the regions north, northeast, central west, south and the southeast of Brazil, respectively. In addition, a total of 425 home appliances were used in the simulations. The results show that the HEMS achieved reductions in the cost of electricity for all the Scenarios used while minimally affecting the satisfaction/comfort of the end consumers as well as taking into account all the restrictions. The largest reduction in the total cost of electricity occurred for the couple without children, resident in the city of Teresina-PI; with a drop from US$ 99.31 to US$ 90.72 totaling 8.65% savings in the electricity bill. Therefore, the results confirm that the proposed HEMS effectively improves the operating efficiency of home appliances and reduces electricity costs for end consumers.
Due to the wide variety of uses and the diversity of features required to meet an application, Internet of Things (IoT) technologies are moving forward at a strong pace to meet this demand while at ...the same time trying to meet the time-to-market of these applications. The characteristics required by applications, such as coverage area, scalability, transmission data rate, and applicability, refer to the Physical and Medium Access Control (MAC) layer designs of protocols. This paper presents a deep study of medium access control (MAC) layer protocols that are used in IoT with a detailed description of such protocols grouped (by short and long distance coverage). For short range coverage protocols, the following are considered: Radio Frequency Identification (RFID), Near Field Communication (NFC), Bluetooth IEEE 802.15.1, Bluetooth Low Energy, IEEE 802.15.4, Wireless Highway Addressable Remote Transducer Protocol (Wireless-HART), Z-Wave, Weightless, and IEEE 802.11 a/b/g/n/ah. For the long range group, Narrow Band IoT (NB-IoT), Long Term Evolution (LTE) CAT-0, LTE CAT-M, LTE CAT-N, Long Range Protocol (LoRa), and SigFox protocols are studied. A comparative study is performed for each group of protocols in order to provide insights and a reference study for IoT applications, considering their characteristics, limitations, and behavior. Open research issues on the topic are also identified.
Celotno besedilo
Dostopno za:
CEKLJ, DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Summary
Corporate insolvency has significant adverse effects on an economy. With the number of multinationals increasing rapidly, corporate bankruptcy can severely disrupt the global financial ...environment. However, multinationals do not fail instantaneously; objective strategies combined with a rigorous analysis of both qualitative and quantifiable data can go a long way in identifying an organization's financial risks. Recent advancements in information and communication technologies have made data collection and storage an easy task. The challenge becomes mining the appropriate data about a company's financial risks and implementing it in forecasting a company's insolvency probabilities. In recent years, machine learning has been incorporated into big data analytics owing to its massive success in learning complex models. Machine learning algorithms such as Support Vector Machines (SVM), Random Forests (RF), Artificial Neural Networks, Gaussian Processes, and Adaptive Learning have been used in the analysis of Big Data to predict the financial risks of companies. In this paper, credit scoring is explored with regards to data processed using the collateral as an independent variable. The obtained results indicate that RF algorithm is promising for use in credit risk management. This research shows the advantages of the RF approach over the SVM algorithm are its speed and operational simplicity, and SVM has the benefit of higher classification accuracy than RF. The paper compares the SVM and RF algorithms to forecast the recovered value in a credit task. The execution of the projected intelligent systems uses tests and algorithms for authentication of the projected model.
•A new method for power quality disturbance detection and classification based on deep learning at the edge.•Deep learning is used for automatic feature extraction and selection.•The proposed ...methodology is embedded in a low-cost smart meter.•Performance evaluation using accuracy, precision, recall and F1-Score.
The large amounts of data collected by smart meters (SM), such as electric energy, water gas consumption and power quality (PQ) metrics, can create a massive flow of data transmitted between consumers and utilities. In this context, an edge-fog-cloud architecture based on a low-cost SM is proposed. The employed SM acquires voltage and current signals to obtain their frequency and amplitude, allowing PQ to be monitored through methods of detection and classification of disturbances in order to send only information about the detected disturbances to the utility, thus reducing network traffic associated with PQ disturbances in Smart Grids. The proposed methodology was embedded at a low-cost SM to enable data exchange with the utility, offering an enormous potential for real scenarios.
The Internet of Things (IoT) is an emerging paradigm that proposes the connection of objects to exchange information in order to reach a common objective. In IoT networks, it is expected that the ...nodes will exchange data between each other and with external Internet services. However, due to deployment costs, not all the network devices are able to communicate with the Internet directly. Thus, other network nodes should use Internet-connected nodes as a gateway to forward messages to Internet services. Considering the fact that main routing protocols for low-power networks are not able to reach suitable performance in the displayed IoT environment, this work presents an enhancement to the Lightweight On-demand Ad hoc Distance-vector Routing Protocol-Next Generation (LOADng) for IoT scenarios. The proposal, named LOADng-IoT, is based on three improvements that will allow the nodes to find Internet-connected nodes autonomously and dynamically, decreasing the control message overhead required for the route construction, and reducing the loss of data messages directed to the Internet. Based on the performed assessment study, which considered several number of nodes in dense, sparse, and mobility scenarios, the proposed approach is able to present significant results in metrics related to quality-of-service, reliability, and energy efficiency.
Among the numerous alternatives used in the world of risk balance, it highlights the provision of guarantees in the formalization of credit agreements. The objective of this paper is to compare the ...achievement of fuzzy sets with that of artificial neural network-based decision trees on credit scoring to predict the recovered value using a sample of 1890 borrowers. Comparing with fuzzy logic, the decision analytic approach can more easily present the outcomes of the analysis. On the other hand, fuzzy logic makes some implicit assumptions that may make it even harder for credit-grantors to follow the logical decision-making process. This paper leads an initial study of collateral as a variable in the calculation of the credit scoring. The study concludes that the two models make modelling of uncertainty in the credit scoring process possible. Although more difficult to implement, fuzzy logic is more accurate for modelling the uncertainty. However, the decision tree model is more favourable to the presentation of the problem.
Ambient gas detection and measurement had become essential in diverse fields and applications, from preventing accidents, avoiding equipment malfunction, to air pollution warnings and granting the ...correct gas mixture to patients in hospitals. Gas leakage can reach large proportions, affecting entire neighborhoods or even cities, causing enormous environmental impacts. This paper elaborates on a deep review of the state of the art on gas-sensing technologies, analyzing the opportunities and main characteristics of the transducers, as well as towards their integration through the Internet of Things (IoT) paradigm. This should ease the information collecting and sharing processes, granting better experiences to users, and avoiding major losses and expenses. The most promising wireless-based solutions for ambient gas monitoring are analyzed and discussed, open research topics are identified, and lessons learned are shared to conclude the study.
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